change j score name

Author: antoinedemathelin

adapt/metrics.py

@@ -413,7 +413,7 @@ def normalized_frechet_distance(Xs, Xt):
     return x_max / Xs.shape[1]
 
 
-def j_score(Xs, Xt, max_centers=100, sigma=None):
+def neg_j_score(Xs, Xt, max_centers=100, sigma=None):
     """
     Compute the negative J-score between Xs and Xt.
     

src_docs/_templates/layout.html

@@ -57,7 +57,7 @@
 <li class="toctree-l1"><a class="reference internal" href="{{ pathto("contents") }}{{ contents }}{{ "adapt-metrics" }}">Metrics</a><ul>
 <li class="toctree-l2"><a class="reference internal" href="{{ pathto("generated/adapt.metrics.make_uda_scorer") }}">make_uda_scorer</a></li>
 <li class="toctree-l2"><a class="reference internal" href="{{ pathto("generated/adapt.metrics.cov_distance") }}">cov_distance</a></li>
-<li class="toctree-l2"><a class="reference internal" href="{{ pathto("generated/adapt.metrics.j_score") }}">j_score</a></li>
+<li class="toctree-l2"><a class="reference internal" href="{{ pathto("generated/adapt.metrics.neg_j_score") }}">neg_j_score</a></li>
 <li class="toctree-l2"><a class="reference internal" href="{{ pathto("generated/adapt.metrics.linear_discrepancy") }}">linear_discrepancy</a></li>
 <li class="toctree-l2"><a class="reference internal" href="{{ pathto("generated/adapt.metrics.normalized_linear_discrepancy") }}">normalized_linear_discrepancy</a></li>
 <li class="toctree-l2"><a class="reference internal" href="{{ pathto("generated/adapt.metrics.frechet_distance") }}">frechet_distance</a></li>

src_docs/contents.rst

@@ -159,7 +159,7 @@ This module contains functions to compute adaptation metrics.
 
    metrics.make_uda_scorer
    metrics.cov_distance
-   metrics.j_score
+   metrics.neg_j_score
    metrics.linear_discrepancy
    metrics.normalized_linear_discrepancy
    metrics.frechet_distance

src_docs/generated/adapt.metrics.j_score.rst

@@ -0,0 +1,8 @@
+:ref:`adapt.metrics <adapt.metrics>`.neg_j_score
+=============================================================
+
+.. currentmodule:: adapt.metrics
+
+.. autofunction:: neg_j_score
+
+	

src_docs/generated/adapt.metrics.neg_j_score.rst

@@ -27,7 +27,7 @@ def test_all_metrics():
     linear_discrepancy(Xs, Xt)
     normalized_linear_discrepancy(Xs, Xt)
     normalized_frechet_distance(Xs, Xt)
-    j_score(Xs, Xt)
+    neg_j_score(Xs, Xt)
     domain_classifier(Xs, Xt)
     domain_classifier(Xs, Xt, LogisticRegression())
     reverse_validation(base_est, Xs, ys, Xt)